Examples of using Data scientists in English and their translations into Hindi
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Facebook might be able to lend some data scientists to its famously lean little brother.
Data scientists say that computer programs,
This second group resists an easy name, but I will call them data scientists.
One barrier to creating these shared standards is that social scientists and data scientists tend to have different approaches to research ethics.
While we're on the topic of flights, data scientists at travel app Hopper have announced that airfares are currently at a three-year low-
Data scientists are highly educated- 88% have at least a Master's degree
These data scientists- who often have training in fields such as computer science,
organizations do not have a ready-made staff of survey gurus, data scientists and behavioral experts who can produce the right survey
Data Scientists are highly educated- 88% have at least a master's degree
It is a given fact that the data scientists are the ones who get higher paying jobs as compared to other engineers
These analytical models allow researchers, data scientists, engineers, and analysts to“produce reliable,
open-source-focused curriculum for students who seek the technical expertise required to become data scientists and analysts, and the business skills to apply this knowledge effectively and strategically.-.
The study predicted a shortfall by 2018 of nearly 200,000 data scientists and 1.5 million managers with the capability to make decisions using big data in the United States alone.
It is for social scientists who want to do more data science, data scientists who want to do more social science,
Public Institutions, Data Scientists design and implement the analysis of big data,
Bit by Bit is for social scientists who want to do more data science, data scientists who want to do more social science,
said‘this is great for your data scientists so that they can go in
In today's data-based world, companies are using the insights that data scientists provide to stay one step ahead of their competition while keeping their overhead costs low.
cyber engineers, risk engineers, data analysts and data scientists.
Most social media analytics platform users are not data scientists, meaning they likely aren't thinking critically about these sorts of questions